Backoff adaptation for digital communication systems with channel quality information

ABSTRACT

System and method for backoff correction of channel quality information (CQI). A correction factor is calculated based on a goodness measure such as packet error rate (PER). The selection of modulation and coding scheme (MCS) is made considering the channel quality information (CQI) adjusted by the correction factor. A meaningful goodness measure can be imposed if the goodness measure is very low. A different correction factor can be calculated for different confidence levels, MCSs and transmission modes.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.13/036,695 filed on Feb. 28, 2011 which claims the benefit of U.S.Provisional Application No. 61/308,959, filed on Feb. 28, 2010 and ofU.S. Provisional Application No. 61/312,553, filed on Mar. 10, 2010, theentire contents of which are incorporated herein by reference.

FIELD OF THE INVENTION

The present invention relates to the field of wireless communication. Inparticular, embodiments of the present invention relate to a method forcorrecting channel quality information estimation for the selection ofmodulation and coding scheme.

BACKGROUND OF THE INVENTION

In digital communication systems that support several modulation andcoding schemes (MCS), the transmitter may have a method for dynamicallyselecting MCS. The problem of dynamic MCS selection is of specialinterest in wireless communication systems, where the channel maysignificantly change over time. For simplicity, the term MCS is usedthroughout this application to encapsulate the combination of modulationand coding scheme (MCS) as well as sampling rate, bandwidth, number ofspatial streams, etc. Two distinct combinations are considered as twodifferent MCS even if they result in the same number of data bits persecond.

Typically, it is desirable for a transmitter to work at, or close to,the maximum possible transmission rate r_(max) of the channel instance,in order to maximize the system throughput. However, working near themaximum transmission rate may be risky. In typical wireless systems,choosing a transmission rate above r_(max) may result in high packeterror rate (PER), which in turn may result in an undesired goodput loss.

Many current MCS selection methods fall in the category of PER-basedtrial and error. Basically, assuming that the transmitter has some shortterm estimation of PER, MCS is changed such that the transmission rateincreases if PER is low enough and changed such that the transmissionrate decreases if PER is too high. A more sophisticated method of thistype is known as the Auto Rate Feedback. While simple, these methodshave relatively poor performance because of their slow settling time,and because they may require long high-PER phases for convergence.

Fast link adaptation methods require that the transmitter have someknowledge of dynamic channel quality information (CQI), e.g., anestimation of signal to noise ratio (SNR) or an effective SNR, for MCSselection. To that matter, CQI may also refer to quantized SNR, or evento MCS recommendation feedback from a receiver, such as that of the fastlink adaptation (FLA) mechanism of the IEEE 802.11n standard. Eachsupported MCS is related to a level of throughput and has a minimumrequired channel quality. The transmitter chooses the MCS with thehighest throughput for which the current quality is above the minimumrequired quality. Clearly, the performance of fast link adaptationmethods relies, inter alia, on the accuracy of the estimated channelquality. If, for example, SNR is used as CQI, then an error in order of1-2 dB in the estimation of SNR may dramatically increase PER.

SUMMARY OF THE INVENTION

According to embodiments of the present invention, there may be provideda method for backoff correction of channel quality information (CQI).The method may include obtaining a goodness measure estimation,calculating a correction factor based on the goodness measure, and usingCQI adjusted by the correction factor for selection of modulation andcoding scheme (MCS).

Furthermore, according to embodiments of the present invention, themethod may include calculating the correction factor by: storing aplurality of tables each describing channel quality dependency on thegoodness measure for one of the MCSs, obtaining current CQI for currentMCS at substantially the same time as the goodness measure estimation,estimating channel quality based on the goodness measure estimation andon a table from the plurality of tables corresponding to the current MCSto get unbiased channel quality estimation, and calculating thecorrection factor by subtracting the unbiased channel quality estimationfrom the current CQI.

Furthermore, according to embodiments of the present invention, themethod may include calculating the correction factor based on a previousvalue of the correction factor and on a correction function relatingcorrection factor changes to goodness measure estimations.

Furthermore, according to embodiments of the present invention, themethod may include having a corresponding correction function for eachMCS.

Furthermore, according to embodiments of the present invention, thecorrection function may be in the form of increasing the correctionfactor by a first constant if the goodness measure estimation may beabove the first threshold, decreasing the correction factor by a secondconstant if the goodness measure estimation may be below the secondthreshold and leave the correction factor unchanged otherwise.

Furthermore, according to embodiments of the present invention, agoodness measure level may be imposed in case the goodness measureestimation substantially equals a minimal goodness measure level, theminimal goodness measure related to MCS having transmission rates belowa maximum supported transmission rate.

Furthermore, according to embodiments of the present invention, thegoodness measure level may be imposed by decreasing the correctionfactor.

Furthermore, according to embodiments of the present invention, thegoodness measure level may be imposed by reducing transmission power.

Furthermore, according to embodiments of the present invention, themethod may include stopping to impose the goodness measure level priorto changing the MCS, and reducing the correction factor by apredetermined value if the goodness measure estimation substantiallyequals a minimal goodness measure level, the minimal goodness measurerelated to MCS having transmission rates below a maximum supportedtransmission rate when a timer expires.

Furthermore, according to embodiments of the present invention, theselection of MCS may be performed based on CQI obtained withnon-decreased transmission power.

Furthermore, according to embodiments of the present invention, themethod may further include assigning confidence levels to packets,assigning a corresponding safety guard to each of the confidence levels,and adding the safety guard to the correction factor.

Furthermore, according to embodiments of the present invention, themethod may further include imposing goodness measure level in case thegoodness measure estimation substantially equals a minimal goodnessmeasure level, the minimal goodness measure related to MCS havingtransmission rates below a maximum supported transmission rate whiletransmitting packets with low confidence level.

Furthermore, according to embodiments of the present invention, thegoodness measure may be selectable from a list comprising: packet errorrate (PER) and a combination of the PER and throughput.

Furthermore, according to embodiments of the present invention, aplurality of the correction factors may be calculated and used, each fora corresponding transmission mode.

Furthermore, according to embodiments of the present invention, themethod may further include calculating and using a plurality of thecorrection factors, each for a corresponding MCS.

Furthermore, according to embodiments of the present invention, themethod may further include filtering the correction factor.

Furthermore, according to embodiments of the present invention, themethod may further include allowing goodness measure levels that resultin data loss in pre-defined periods in which valuable data may be nottransmitted.

According to embodiments of the present invention there may be providedsystem for backoff correction of channel quality information (CQI). Thesystem may include a CQI estimation module that may obtain CQI, abackoff adaptation module that may get a goodness measure estimation andmay calculate a correction factor based on the goodness measure, and amodulation and coding scheme (MCS) selection module that may use the CQIadjusted by the correction factor for selection of MCS.

Furthermore, according to embodiments of the present invention, whereinthe backoff adaptation module may calculate the correction factor bystoring a plurality of tables each describing channel quality dependencyon the goodness measure for one of the MCSs, obtaining current CQI fromthe CQI estimation module for current MCS at substantially the same timeas the goodness measure estimation, estimating channel quality based onthe goodness measure estimation and on a table taken from the pluralityof tables corresponding to the current MCS to get unbiased channelquality estimation, and calculating the correction factor by subtractingthe unbiased channel quality estimation from the current CQI.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may calculate the correction factor based on aprevious value of the correction factor and on a correction functionrelating correction factor changes to goodness measure estimations.

Furthermore, according to embodiments of the present invention, each MCSmay have a corresponding correction function.

Furthermore, according to embodiments of the present invention, thecorrection function may be in the form of increasing the correctionfactor by a first constant if the goodness measure estimation may beabove the first threshold, decreasing the correction factor by a secondconstant if the goodness measure estimation may be below the secondthreshold and leave the correction factor unchanged otherwise.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may impose a goodness measure level in casethe goodness measure estimation substantially equals a minimal goodnessmeasure level, the minimal goodness measure related to MCS havingtransmission rates below a maximum supported transmission rate.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may impose a goodness measure level bydecreasing the correction factor.

Furthermore, according to embodiments of the present invention, thesystem may include at least one gain block that may amplify power of atleast one signal transmitted by at least one antenna according to acontrol signal received from the backoff adaptation module, wherein thebackoff adaptation module may impose a goodness measure level bychanging the control signal and thus changing transmission power.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may further stop imposing the goodness measurelevel prior to changing the MCS, and reduce the correction factor by apredetermined value if the goodness measure estimation substantiallyequals a minimal goodness measure level, the minimal goodness measurerelated to MCS having transmission rates below a maximum supportedtransmission rate when the timer expires.

Furthermore, according to embodiments of the present invention, thesystem may include

Furthermore, according to embodiments of the present invention, the MCSselection module may use CQI obtained with non-decreased transmissionpower for the selection of MCS.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may obtain confidence levels assigned topackets, assign a corresponding safety guard to each of the confidencelevels, and add the safety guard to the correction factor.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may impose goodness measure level in case thegoodness measure estimation substantially equals a minimal goodnessmeasure level, the minimal goodness measure related to MCS havingtransmission rates below a maximum supported transmission rate whiletransmitting packets with low confidence level.

Furthermore, according to embodiments of the present invention, thegoodness measure may be selectable from a list comprising: packet errorrate (PER) and a combination of the PER and throughput.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may calculate and use a plurality of thecorrection factors, each for a corresponding transmission mode.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may calculate and use a plurality of thecorrection factors, each for a corresponding MCS.

Furthermore, according to embodiments of the present invention, thesystem may include a filter to filter the correction factor.

Furthermore, according to embodiments of the present invention, thebackoff adaptation module may impose a goodness measure levels thatresult in data loss in pre-defined periods in which valuable data may benot transmitted.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter regarded as the invention is particularly pointed outand distinctly claimed in the concluding portion of the specification.The invention, however, both as to organization and method of operation,together with objects, features, and advantages thereof, may best beunderstood by reference to the following detailed description when readwith the accompanying drawings in which:

FIG. 1 schematically illustrates a module diagram of a wirelesscommunication system utilizing backoff adaptation according toembodiments of the present invention;

FIG. 2 is a flowchart illustration of a method for backoff correction ofchannel quality information (CQI) according to embodiments of thepresent invention;

FIG. 3 schematically illustrates an exemplary curve relating packeterror rate (PER) and signal to noise ratio (SNR) for a given rateaccording to embodiments of the present invention;

FIG. 4 schematically illustrates an exemplary correction functionaccording to embodiments of the present invention;

FIG. 5 schematically illustrates an exemplary block diagram of a moduleadapted to perform closed-loop backoff adaptation (CLBA) according toembodiments of the present invention;

FIG. 6 schematically illustrates an exemplary block diagram of atransmitter capable of controlling transmission power during trackingphase according to embodiments of the present invention;

FIG. 7 is a flowchart illustration of a method for protected backoffcorrection of CQI according to embodiments of the present invention; and

FIG. 8 schematically illustrates an exemplary block diagram of a moduleadapted to perform protected CLBA according to embodiments of thepresent invention.

It will be appreciated that for simplicity and clarity of illustration,elements shown in the figures have not necessarily been drawn to scale.For example, the dimensions of some of the elements may be exaggeratedrelative to other elements for clarity. Further, where consideredappropriate, reference numerals may be repeated among the figures toindicate corresponding or analogous elements.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

In the following detailed description, numerous specific details are setforth in order to provide a thorough understanding of the invention.However, it will be understood by those skilled in the art that thepresent invention may be practiced without these specific details. Inother instances, well-known methods, procedures, and components have notbeen described in detail so as not to obscure the present invention.

Although embodiments of the present invention are not limited in thisregard, discussions utilizing terms such as, for example, “processing,”“computing,” “calculating,” “determining,” “establishing”, “analyzing”,“checking”, or the like, may refer to operation(s) and/or process(es) ofa computer, a computing platform, a computing system, or otherelectronic computing device, that manipulate and/or transform datarepresented as physical (e.g., electronic) quantities within thecomputer's registers and/or memories into other data similarlyrepresented as physical quantities within the computer's registersand/or memories or other information storage medium that may storeinstructions to perform operations and/or processes.

Although embodiments of the present invention are not limited in thisregard, the terms “plurality” and “a plurality” as used herein mayinclude, for example, “multiple” or “two or more”. The terms “plurality”or “a plurality” may be used throughout the specification to describetwo or more components, devices, elements, units, parameters, or thelike. Unless explicitly stated, the method embodiments described hereinare not constrained to a particular order or sequence. Additionally,some of the described method embodiments or elements thereof can occuror be performed at the same point in time.

Throughout the specification PER values are presented in normalizedvalues linearly ranging from 0 to 1 wherein 0 stands for no packet lossand 1 stands for 100% packet loss in a given time interval.

It should be understood that the present invention may be used in avariety of applications. Although the present invention is not limitedin this respect, the circuits and techniques disclosed herein may beused in many apparatuses such as personal computers, stations of a radiosystem, wireless communication system, digital communication system,satellite communication system, and the like.

Stations intended to be included within the scope of the presentinvention include, by way of example only, wireless local area network(WLAN) stations, wireless personal area network (WPAN) stations, two-wayradio stations, digital system stations, analog system stations,cellular radiotelephone stations, and the like.

Types of WLAN communication systems intended to be within the scope ofthe present invention include, although are not limited to, “IEEE-Std802.11, 1999 Edition (ISO/IEC 8802-11: 1999)” standard, and moreparticularly in “IEEE-Std 802.11b-1999 Supplement to 802.11-1999,Wireless LAN MAC and PHY specifications: Higher speed Physical Layer(PHY) extension in the 2.4 GHz band”, “IEEE-Std 802.11a-1999, Higherspeed Physical Layer (PHY) extension in the 5 GHz band” standard, “IEEEStd 802.11n-2009,” IEEE 802.11ac standard (e.g., as described in “IEEE802.11-09/0992r21”) and the like.

Types of WLAN stations intended to be within the scope of the presentinvention include, although are not limited to, stations for receivingand transmitting spread spectrum signals such as, for example, FrequencyHopping Spread Spectrum (FHSS), Direct Sequence Spread Spectrum (DSSS),Orthogonal Frequency-Division Multiplexing (OFDM) and the like.

Devices, systems and methods incorporating aspects of embodiments of theinvention are also suitable for computer communication networkapplications, for example, intranet and Internet applications.Embodiments of the invention may be implemented in conjunction withhardware and/or software adapted to interact with a computercommunication network, for example, a local area network (LAN), a widearea network (WAN), or a global communication network, for example, theInternet.

According to embodiments of the present invention MCS selection at thetransmitter may be based, inter alia, on channel quality. The channelquality may be seen as composed of two components: estimated CQI, alsoreferred to as fast-varying component and a bias or error component. Thebias may typically be substantially constant or slowly-varyingcomponent. The fast-varying component may depend on the dynamics of thephysical channel. For example, the fast-varying component may change incase a person is walking between a transmitter and a receiver in awireless system. The slowly-varying component may depend on constantunknown gains of amplifiers, slow gain variation of amplifiers withtime, slow variation of receiver noise figure with time, etc.

According to embodiments of the present invention the fast-varyingcomponent of the channel quality may be estimated by the transmitter bymeasuring instantaneous CQI, for example, by estimating SNR or effectiveSNR, quantized SNR, or MCS recommendation feedback from a receiver, suchas that of the fast link adaptation (FLA) mechanism of the IEEE 802.11nstandard. The slowly-varying component, however, may be seen as a biasor error in the estimation of CQI.

Thus, according to embodiments of the present invention the estimationof CQI, e.g., SNR or effective SNR made by the transmitter may includean error component that may vary with time. For example, SNR oreffective SNR may be estimated during a training sessions in which thereceiver transmits known data sets to the transmitter, e.g., as in theimplicit feedback mode of the 802.11n standard. SNR, or effective SNR,may be estimated by the transmitter based on the received data as wellas on receiver characteristics such as uplink TX power and noise figureof the receiver. Since the receiver characteristics are typically notknown to the transmitter, the transmitter makes assumptions of thesereceiver characteristics. Errors in the assumptions of the TX power andthe noise figure of the receiver may cause an error in the estimation ofCQI. Since the TX power and the noise figure may change slowly withtime, the error in the estimation of CQI may vary slowly with time aswell. Alternatively, CQI may be estimated by the receiver and reportedto the transmitter in a control channel, as in the explicit feedbackmode of the 802.11n standard, or in the fast link adaptation (FLA)mechanism of the 802.11n standard, where returned MCS recommendationsmay be considered as quantized SNR feedback, or in the link adaptationmechanism of 802.1ac, where the receiver returns both MCS and SNR, andthe CQI is therefore a combination of both. If the receiver bases thecalculation on an RX power measurement, then the receiver has to havesome assumptions on its own noise figure. Again, an error in theassumption of the receiver noise figure can cause an error or bias inthe assumption of CQI.

As known to these skilled in the art, in many practical situations themain bulk of error in the estimation of CQI may be constant or may varyslowly with time, with relation to changes in CQI

According to embodiments of the present invention the bias or error inthe estimation of CQI can be compensated by adding an appropriatecorrection factor, also referred to as backoff, B, to the estimated CQI,therefore receiving corrected CQI, q_(corr).

Reference is made to FIG. 1 which schematically illustrates a modulediagram of a wireless communication system 100 utilizing backoffadaptation according to embodiments of the present invention. Accordingto embodiments of the present invention, system 100 may comprise atransmitter 110 transmitting data to receiver 140 through wirelesscommunication channel 130. Transmitter 110 and receiver 140 may include,for example, a wireless communication station or a wirelesscommunication device able to transmit and/or receive wirelesscommunication signals. It should be noted that while transmitter 110 andreceiver 140 are presented with relation to the main data transmissiondirection in a given session, both stations may have transition andreception capabilities.

According to embodiments of the present invention, transmitter 110 mayinclude a MCS selection module 116, a CQI estimation module 112, backoffadaptation module 114 and antenna 118.

MCS selection module 116 may be adapted to set MCS based on a q_(corr).For example, MCS selection module 116 may hold a table relatingsupported MCSs with minimum required channel quality. MCS selectionmodule 116 may choose the MCS with substantially maximum throughput forwhich current q_(corr) is above the respective minimum required quality.

CQI estimation module 112 may estimate CQI by any applicable method, asknown in the art. For example, CQI estimation module 112 may estimateCQI by initiating training sessions in which receiver 140 may transmitknown data sets to transmitter 110, as in the implicit feedback mode ofthe IEEE 802.11n standard. CQI estimation module 112 may estimate CQIbased on the received data as well as on characteristics of receiver 140such as TX power and noise figure of receiver 140. As mentioned above,the characteristics of receiver 140 are typically not known to CQIestimation module 112, and thus, CQI estimation module 112 may makeassumptions of these characteristics. Errors in the assumptions of theTX power and the noise figure of receiver 140 may cause an error in theestimation of CQI. Alternatively, CQI estimation module 112 may receiveCQI estimations made by receiver CQI estimation module 142 andtransmitted over channel 130, as in the explicit feedback mode of the802.11n standard.

According to embodiments of the present invention, receiver 140 mayinclude a receiver CQI estimation module 142, and antenna 148. ReceiverCQI estimation module 142 may estimate CQI by, for example, trainingsessions in which transmitter 110 may transmit known data sets toreceiver 140. Receiver CQI estimation module 142 may estimate CQI basedon the received data as well as on characteristics of receiver 140 suchas the noise figure of receiver 140. As mentioned above, the noisefigure of receiver 140 is typically not known to receiver CQI estimationmodule 142, and thus, receiver CQI estimation module 142 may makeassumptions of its own noise figure. Errors in the assumption of thenoise figure of receiver 140 may cause an error in the estimation ofCQI. Receiver 140 may transmit the CQI estimation of CQI estimationmodule 142 to transmitter 110, and this CQI estimation may serve as theinput to MCS selection module 116 instead of the output of channelquality information estimation module 112.

Although the invention is not limited in this respect, antennas 118, 148may include, for example, a set of N antennas. Antennas 118, 148 mayinclude, for example, an internal and/or external RF antenna, e.g., adipole antenna, a monopole antenna, an omni-directional antenna, an endfed antenna, a circularly polarized antenna, a micro-strip antenna, adiversity antenna, or any other type of antenna suitable fortransmitting and/or receiving wireless communication signals, modules,frames, transmission streams, packets, messages and/or data.

According to embodiments of the present invention backoff adaptationmodule 114 is adapted to obtain goodness measure estimations, forexample PER estimations, and calculate time dependant estimation of thebackoff, B, based on the goodness measure. Backoff adaptation module 114may be implemented using any suitable combination of memory, hardwiredlogic, and/or general-purpose or special-purpose processors, as is knownin the art.

PER estimation may be obtained in many different ways. For example, insystems supporting an acknowledgement protocol, transmitter 110 maycompare the number of acknowledged packets to the total number oftransmitted packets. It should be noted that PER is just one possiblegoodness measure for updating the backoff, and the backoff updates maybe based on many other goodness measures e.g., a combination of PER andthroughput. For simplicity, PER will be used throughout thespecification to mean any such goodness measure.

According to embodiments of the present invention in between updates ofbackoff, B, MCS selection module 116 may base MCS selection on the timevarying value of CQI, {circumflex over (q)}(t), adjusted by B.Specifically, MCS selection module 116 may use

q _(corr)(t)={circumflex over (q)}(t)−B,  (1)

instead of {circumflex over (q)}(t) for MCS selection. It should benoted that in (1) as well as subsequent formulae the CQI and the backoffare given in dB units.

Reference is now made to FIG. 2 which is a flowchart illustration of amethod for backoff correction of CQI according to embodiments of thepresent invention. According to embodiments of the present invention, apredefined value of backoff, B_(Initial), may be initiated, as indicatedin block 210. B_(initial) may be calculated in a post-productioncalibration process, or alternatively may be set to a pre-estimatedvalue based on any assumptions on the unknown parameters, such as the TXpower of the receiver 140, the noise figure of the receiver 140, etc.Alternatively, B_(initial) may be set to zero. During tracking phases,backoff B may be calculated based on PER estimations, as indicated inblocks 220 and 230. Exemplary methods for backoff calculations will bediscussed in detail infra. At block 240 the input to MCS selection blockmay be set to CQI shifted or adjusted by the backoff, for example,according to equation 1. Although embodiments of the invention are notlimited in this respect, the method depicted in FIG. 2 may be performedby embodiments of the present invention, for example, an embodiment asshown in FIG. 1.

According to embodiments of the present invention the backoff may beestimated using curve-based method. Typically, the system PER may be afunction of channel quality, q, MCS, and additional transmissionparameters such as packet length, demodulation method, decoding method,etc. To simplify notation, it is assumed that all these additionaltransmission parameters are fixed, and hence PER may be a function ofchannel quality and MCS. It follows that for each fixed MCS, PER may bea function of channel quality. Typically, this function may beinvertible, and hence for each fixed MCS, channel quality may bepresented as a function of PER. It should be noted that embodiments ofthe present invention are not limited to having the additionaltransmission parameters fixed and may include varying packet length,demodulation method, decoding method etc.

According to embodiments of the present invention a plurality offunctions or tables describing channel quality dependency on PER forsupported MCSs, q_(MCS)(PER) may be held by or accessible from, forexample, backoff adaptation module 114. For example, if SNR is used aschannel quality indicator, q, then backoff adaptation module 114 mayhold a plurality of functions or tables describing the SNR dependency onPER for supported MCS, SNR_(MCS)(PER). According to embodiments of thepresent invention the functions or tables relating channel quality toPER for supported MCS, q_(MSC)(PER) may be estimated or measured offlineand stored, for example, in backoff adaptation module 114.

In typical digital communication systems, PER vs. SNR curves may have asteep “waterfall” shape. This means that typically, PER may be eithernearly 0 for high SNR values, or nearly 1 for low SNR values with aslope in a subinterval I⊂[0,1] of PER. Relating channel quality to PERrequires working in the subinterval I of PER in which a measurablechange in SNR will result in a measurable change in PER. Estimations ofPER falling within subinterval I are referred to meaningful PERestimations throughout the specification. In practice, the subintervalof meaningful PER estimations may be affected by several factors, suchas length of PER estimation window, PER floors due to impairments thatare unaccounted for, sensitivity of the q_(MCS)(PER) function to errors,etc. As a practical example, when PER is estimated based on several tensof packets, choosing I=[0.05,0.5] may give substantially goodestimations of q_(rate)(PER).

Reference is made to FIG. 3 which schematically illustrates an exemplarycurve 300 relating PER and SNR for a given MCS according to embodimentsof the present invention. Point 330 denotes estimated current CQI attime t₀, {circumflex over (q)}(t₀), and point 310 denotes a currentgoodness measure such as meaningful PER estimation received at time t₀,{circumflex over (p)}(t₀). Point 320 may be an unbiased channel qualityestimation, q_(MCS)({circumflex over (p)}(t₀)). According to embodimentsof the present invention q_(MCS) ({circumflex over (p)}(t₀)) may be seenas an estimation of channel quality that includes the two components:estimated CQI, {circumflex over (q)}(t₀), as well as the bias or errorcomponent. Thus, the backoff, B, may be related to the differencebetween {circumflex over (q)}(t₀) and q_(MCS) ({circumflex over (p)})such that

B={circumflex over (q)}(t ₀)−q _(MCS)({circumflex over (p)}(t ₀)),  (2)

According to embodiments of the prevent invention, the backoff Bobtained using Equation (2) may be further filtered. Such filtering mayinclude FIR filtering, BR filtering etc. One example of IIR filtering isthe use of a “forgetting factor” α to set B₁₊₁=αB+(1−α)B_(i), where B isobtained from (2), B_(i) may be a previous value of B, while B_(i+1) maybe a next value of B.

According to embodiments of the present invention the backoff may beestimated based on closed-loop backoff adaptation (CLBA) method.According to CLBA method PER may be tracked while MCS selection is basedon the backoff-corrected CQI, and the backoff may be updated accordingto PER: When the PER is too high the backoff may be increased, whilewhen the PER is sufficiently low the backoff may be decreased. Accordingto CLBA, PER, which depends on the previous backoff, is fed-back toupdate the backoff. A correction function or {circumflex over(p)}→ΔB({circumflex over (p)}) relating the backoff change ΔB for agiven PER estimation {circumflex over (p)} may be stored, for example,at backoff adaptation module 114. The correction function or table maydepend on MCS, such that different correction functions will be fittedto different MCSs. When a new PER estimation {circumflex over (p)} isavailable, the backoff, B, may be updated according to:

B←B _(prev) +ΔB({circumflex over (p)}).  (3)

Where B_(prev) denotes the previous value of B.

Reference is made to FIG. 4 which schematically illustrates an exemplarycorrection function according to embodiments of the present invention.According to the correction function presented in FIG. 4 the backoffchange may be a positive constant Δ₁ if {circumflex over (p)}≧th_(↑), anegative constant (−Δ₂), where Δ₂>0, if {circumflex over (p)}≦th_(↓),and zero otherwise. According to the correction function presented inFIG. 4 in some embodiments of the invention there may be no need for atable of values for describing function {circumflex over(p)}→ΔB({circumflex over (p)}); the constants Δ₁, Δ₂, th_(↑), th_(↓) maybe sufficient. For a non-smooth correction function as that of FIG. 4, Bmay not change smoothly with time. However, B may jitter around a slowlyvarying, smooth function. It should be readily understood to thoseskilled in the art that many other correction functions or tables may besuitable.

Reference is made to FIG. 5 which schematically illustrates an exemplaryblock diagram of a module 500 adapted to perform CLBA according toembodiments of the present invention. Module 500 may include MCSselection module 116, and backoff adaptation module 114. Backoffadaptation module 114 may include correction function block 510, filter540 and adders 520 and 530. According to embodiments of the presentinvention correction function block 510 may calculate backoff change ΔBbased on PER estimate {circumflex over (p)} and on the current MCS.Backoff change ΔB may be added to the previous value of backoff, Bprev,by adder 520 to get the current backoff value, B. The backoff, B, may besubtracted from time varying value of CQI, {circumflex over (p)}(t), toget a q_(corr) according to formula 1 by adder 530. MCS selection module116 may get q_(corr) for MCS selection.

According to embodiments of the prevent invention, the backoff Bobtained after adder 520 may be further filtered before transferred toadder 530. Such filtering may include any known in the art low pass orband pass filtering such as FIR filtering, IIR filtering etc. Oneexample of IIR filtering is the use of a “forgetting factor” α to setB_(i+1)=αB+(1−α)B_(i), where B is obtained from adder 520, B_(i) is aprevious value of B fed to adder 530, while B_(i+1) may be a next valueof B fed to adder 530.

According to embodiments of the present invention a positive bias inq_(corr) may be thought of as Optimism bias, since MCS selection module116 mistakenly acts as if the channel quality is better than it reallyis. In this situation, MCS selection module 116 tends to select an MCSwith overly high data transmission rate, resulting in increased PERlevels. Thus, a positive bias in a q_(corr) may manifest itself in theform of high PER. Moreover, the larger the positive bias in a q_(corr),the larger the PER, since higher unsupported transmission data rates arechosen more frequently. A negative bias in q_(corr), on the other hand,may be thought of as pessimism bias. In this case, MCS selection module116 may tend to select MCS with transmission rates below the maximumsupported rate.

According to embodiments of the present invention a positive bias inq_(corr) may be corrected in the normal operation of backoff estimation.According to curve-based method, high levels of PER may simply result ina relatively high backoff. This may be true also for PER levels that areabove the meaningful PER interval I. In case the PER is above themaximum meaningful PER, it may be treated as a meaningful PER and acorresponding backoff may be calculated. The backoff may continue toincrease, until eventually the transmission rate may be low enough sothat PER may be within the meaningful interval. According to CLBAmethod, high PER values may result in higher backoff values, based onthe correction function. For example, according to the correctionfunction presented in FIG. 4, PER values above th_(↑) may result inincrease in B by Δ₁.

According to embodiments of the present invention a negative bias inq_(corr) may be overlooked since a negative bias in a q_(corr) mayresult in a very low, for example, below 0.01, or substantially zero PERlevels. For many communication systems, selecting MCS having the maximumsupported transmission rate has substantially the same effect on PER asselecting MCS having transmission rates below the maximum supportedtransmission rate. Thus, negative bias in a q_(corr) may be problematicsince the transmitter may not use the available throughput and not getan indication of this via PER. To avoid situations of overlookednegative bias in q_(corr), low levels of PER may be imposed during thetracking phase in order to distinguish between the case where thebackoff is correct, and the case where the backoff is too high. Thus,low levels of PER may be imposed in case the goodness measure estimationsubstantially equals a minimal goodness measure level related to MCShaving transmission rates below the maximum supported transmission rate.Such low levels of PER may be, for example, 0.05-0.1, that is 5 to 10percent packet loss in a time interval. Keeping PER below 0.1 may enablemost wireless protocols to compensate for the lost packets by, forexample, retransmission.

According to CLBA method, situations of overlooked negative bias inq_(corr) may be avoided, for example, by choosing a correction functionthat will decrease the backoff, B, in cases of low PER levels. Forexample, according to the correction function presented in FIG. 4, PERvalues below th_(↓) may result in decrease in B by Δ₂. Such a correctionmay eventually impose PER, since the selected MCS may increase as longas the PER is too low.

According to curve-based method, situations of overlooked negative biasin q_(corr) may be avoided, for example, by imposing PER in order todistinguish between the case where the backoff is correct, and the casewhere the backoff is too high. Imposing PER may be achieved by, forexample, reducing the transmission power. Reduction in the transmissionpower may be achieved by several different techniques, such as digitallymultiplying the baseband signal by an appropriate factor, digitallycontrolling analog power amplifiers, etc. Once the transmission power islow enough, PER may increase to the meaningful interval, and the backoffmay be extracted.

Reference is made to FIG. 6 which schematically illustrates an exemplaryblock diagram of a transmitter 600 capable of controlling transmissionpower during tracking phase according to embodiments of the presentinvention. According to embodiments of the present invention transmitter600 may include a MCS selection module 116, backoff adaptation module114 gain blocks 610 timer 620 and antennas 118. Each of gain blocks 610may be connected to one of antennas 118 and may amplify the power of thesignal transmitted by the antenna according to a control signalreceived, for example, from backoff adaptation module 114. Gain block610 may include analog power amplifiers, may be implemented digitally orbe a combination of both. According to embodiments of the presentinvention backoff adaptation module 114 may control the amplificationlevel of gain blocks 610 by changing the control signal and thus mayreduce and increase the transmission power as discussed above.

It should be noted that both CLBA and curve-based methods may impose PERby either decreasing the backoff or by decreasing the transmissionpower, or by any other applicable method. For example, decreasing thetransmission power may be combined with decreasing the backoff. Forexample, transmission power may be reduced if PER levels are below aselected threshold. However, to avoid PER during MCS changes, it may bepossible to stop imposing PER levels prior to changing the MCS, forexample, by returning to full transmission power prior to MCS changes,for example backoff adaptation module 114 may impose full transmissionpower prior to MCS changes by changing the control signal of gain blocks610, and then re-start the gradual power decrement in the new MCS. IfCQI, and hence the selected MCS, change very rapidly, the system may nothave sufficient time between MCS changes to reduce the power enough toget a meaningful PER. To overcome this problem, it is possible, e.g., tointroduce a timer dependant reduction in the backoff. If there were nomeaningful PER readings when timer 620 expires, the backoff may bereduced by a pre-defined value.

According to embodiments of the present invention to enable PER growthwith power reduction, MCS selection module 116 should not receiveindication of the power reduction, so that MCS selection module 116 willmaintain the current MCS even when MCS selection module 116 wouldnormally select a MCS with lower transmission rate with the lower power.This may apply to systems that consider also transmission power for theselection of MCS, as the transmission power directly effect {circumflexover (q)}(t). Hence, MCS selection may be based on {circumflex over(q)}(t)−B where {circumflex over (q)}(t) is the channel quality with theoriginal, non-decreased, power.

According to embodiments of the present invention, to get a fastestimation of the backoff, it is possible to allow higher values of PER,e.g., PER levels that may result in data loss, that is PER levels abovethe level easily corrected by the system by, for example,retransmission, for example, PER levels above 0.1, in pre-definedperiods in which valuable data is not transmitted. Such a pre-definedperiod may be, for example, at system start-up. The pre-defined periodsin which relatively high PER is allowed will be referred to asacquisition periods throughout the application. During acquisitionperiods, it may be possible to combine an MCS scan followed by powerreductions in order to minimize the time required to get into thedesired PER interval I. For example, during acquisition periods, thebackoff adaptation module may work as follows:

1. Start transmission with some pre-defined MCS, e.g., the highest MCS,and decrease the MCS index until the first time the PER is within thedesired interval I or below it.2. If the PER at the final MCS is within I, then use the tablecorresponding to the final MCS to calculate the backoff.3. Otherwise, if the PER at the final MCS is below I, start reducingpower until the PER is within I or above it. Once the PER is within I orabove it, use the table corresponding to the final MCS in order tocalculate the backoff.

According to embodiments of the present invention an initial value ofbackoff, B_(initial), may be calculated based on information gatheredduring a post-production calibration process. In post-productioncalibration process various quantities influencing the constant bias on{circumflex over (q)}(t) may be measured or estimated, such as thereceiver noise figure, the difference between the TX power oftransmitter 110 and that of the receiver 140 in a reversed trainingsession, etc. B_(initial) may be set to compensate for the bestpost-production bias estimate. Alternatively, B₀ may be set to zero.

As mentioned above, in cases PER values are very low the transmitter mayintroduce low but meaningful PER level to distinguish between negativeand zero bias in {circumflex over (q)}(t) during the tracking phase. Insome cases, it may be desirable that at least some of the packetstransmitted with the highest quality possible, without deliberatelyintroducing any level of errors. Thus, the packets may be divided into Nconfidence levels. Each confidence level i may be characterized by itsown safety guard, B_(i), iε{0, . . . , N−1}. Safety guard B_(i) may bean additional, predetermined backoff level fitted to each confidencelevel, which may be used on top of the tracked backoff B. MCS selectionmodule 116, when deciding on the MCS of packets of confidence level i,may use as the channel quality vector q_(corr,i):

q _(corr,i) ={circumflex over (q)}(t)−B−B _(i)  (4)

To avoid introduction of errors while transmitting packets with highconfidence level, meaningful PER levels may be induced, if needed, whiletransmitting packets with low confidence level. For example, meaningfulPER levels may be induced during PER confidence level, also referred toas PER class. For ease of presentation, the PER class will be givenindex 0, so that B₀ corresponds to the PER class. Note that choosingB₀≠0 will simply shift the tracked backoff B, and therefore B₀ may beset to 0. According to embodiments of the present invention, the backofffor packets in protection class 0, may be the backoff B calculated asdescribed hereinabove, while packets in protection class i, iε{1, . . ., N−1}, may have higher backoff levels, depending on B_(i). Backoffcorrection of CQI with confidence levels may be referred to as protectedbackoff correction of CQI. When N=1, protected backoff correction of CQIcoincides with backoff correction of CQI.

Reference is now made to FIG. 7 which is a flowchart illustration of amethod for protected backoff correction of CQI according to embodimentsof the present invention. Although embodiments of the invention are notlimited in this respect, method depicted in FIG. 7 may be performed byembodiments of the present invention, for example, an embodiment asshown in FIG. 1.

According to embodiments of the present invention, a predefined value ofbackoff, B_(initial), may be initiated, as indicated in block 710.B_(initial) may be calculated in a post-production calibration process,or alternatively may be set to zero. During tracking phases, backoff Bmay be calculated based on the current MCS and on meaningful PERestimations which are received, for example, during PER class, asindicated in blocks 720 and 730. Alternatively, backoff B may becalculated based on substantially all PER estimations, however PERvalues may be imposed only during PER class. At block 740 the input tothe MCS selection block may be set to vector {{circumflex over(q)}(t)−B−B_(i)}_(i=0) ^(N-1). For selecting the MCS of followingpackets in confidence level i, the i^(th) entry of this vector may beused.

Reference is made to FIG. 8 which schematically illustrates an exemplaryblock diagram of a module 800 adapted to perform protected CLBAaccording to embodiments of the present invention. Module 800 mayinclude MCS selection module 116, and backoff adaptation module 114.Backoff adaptation module 114 may include correction function block 820and adders 520, 530 and 810. According to embodiments of the presentinvention correction function block 820 may calculate backoff change ΔBbased on PER estimation {circumflex over (p)} which are received, forexample, during PER class, and on the current MCS. Backoff change ΔB maybe added to the previous value of backoff, Bprev, by adder 520 to getthe current backup value, B. The backoff, B, may be subtracted from timevarying value of CQI, {circumflex over (q)}(t), by adder 530. Adders 810may further subtract Safety guard B_(i) to get q_(corr,i) according toequation (4). MCS selection module 116 may get q_(corr) for MCSselection. Thus, according to embodiments of the present invention thebackoff shifted values of CQI are further shifted by safety guardvector, B_(i), for packets in various confidence levels.

According to embodiments of the present invention meaningful PERestimations are received less frequently than CQI estimations. Forexample, CQI estimations may be received every 1-20 msec whilemeaningful PER estimations may be received every 1-5 seconds. Combiningthe relatively slowly varying backoff estimations with CQI may have thefollowing advantages: The backoff tracking, while slower than thechannel variations, is fast enough to substantially track the error orbias component in the channel quality figure. The use of {circumflexover (q)}(t) may enable MCS selection module 116 to detect fast channelvariations, and make an appropriate MCS selection.

Backoff, B, may have different values for different transmission modes,where transmission mode may be combination of factors such as bandwidth,e.g. 20/40 MHz in 802.11n, length of guard interval in 802.11n, whethera space/time block code (STBC) is used, etc. As known in the art,transmission mode may change rapidly. For example, according to the802.11n standard transmission mode may change from frame to frame.According to embodiments of the present invention, the system, forexample, backoff adaptation module 114, may store and track the backoffper-transmission mode such that different supported transmission modesmay have different backoff values, wherein these different backoffvalues may be tracked and calculated during transmission in thecorresponding transmission mode. During operation, CQI may be adjustedby the backoff level corresponding to the current transmission mode.

Some embodiments of the present invention may be implemented in softwarefor execution by a processor-based system, for example, backoffadaptation module 114. For example, embodiments of the present inventionmay be implemented in code and may be stored on a nontransitory storagemedium having stored thereon instructions which can be used to program asystem to perform the instructions. The storage medium may include, butis not limited to, any type of disk including floppy disks, opticaldisks, compact disk read-only memories (CD-ROMs), rewritable compactdisk (CD-RW), and magneto-optical disks, semiconductor devices such asread-only memories (ROMs), random access memories (RAMs), such as adynamic RAM (DRAM), erasable programmable read-only memories (EPROMs),flash memories, electrically erasable programmable read-only memories(EEPROMs), magnetic or optical cards, or any type of media suitable forstoring electronic instructions, including programmable storage devices.Other implementations of embodiments of the present invention maycomprise dedicated, custom, custom made or off the shelf hardware,firmware or a combination thereof.

Embodiments of the present invention may be realized by a system thatmay include components such as, but not limited to, a plurality ofcentral processing units (CPU) or any other suitable multi-purpose orspecific processors or controllers, a plurality of input units, aplurality of output units, a plurality of memory units, and a pluralityof storage units. Such system may additionally include other suitablehardware components and/or software components.

While certain features of the invention have been illustrated anddescribed herein, many modifications, substitutions, changes, andequivalents will now occur to those of ordinary skill in the art. It is,therefore, to be understood that the appended claims are intended tocover all such modifications and changes as fall within the true spiritof the invention.

What is claimed is:
 1. A method for backoff correction of channelquality information (CQI), the method comprising: obtaining a goodnessmeasure estimation; calculating a correction factor based on saidgoodness measure; and using CQI adjusted by said correction factor forselection of modulation and coding scheme (MCS).
 2. The method of claim1 wherein said correction factor is calculated by: storing a pluralityof tables each describing channel quality dependency on said goodnessmeasure for one of said MCSs; obtaining current CQI for current MCS atsubstantially the same time as said goodness measure estimation;estimating channel quality based on said goodness measure estimation andon a table from said plurality of tables corresponding to said currentMCS to get unbiased channel quality estimation; and calculating saidcorrection factor by subtracting said unbiased channel qualityestimation from said current CQI.
 3. The method of claim 1 whereincalculating said correction factor is based on a previous value of saidcorrection factor and on a correction function relating correctionfactor changes to goodness measure estimations.
 4. The method of claim 3wherein each MCS has a corresponding correction function.
 5. The methodof claim 3 wherein the correction function is in the form of increasingsaid correction factor by a first constant if said goodness measureestimation is above said first threshold, decreasing said correctionfactor by a second constant if said goodness measure estimation is belowsaid second threshold and leave said correction factor unchangedotherwise.
 6. The method of claim 1 wherein a goodness measure level isimposed in case said goodness measure estimation is substantially lessthan or equal to a minimal goodness measure level.
 7. The method ofclaim 6 wherein said goodness measure level is imposed by decreasingsaid correction factor.
 8. The method of claim 6 wherein said goodnessmeasure level is imposed by reducing transmission power.
 9. The methodof claim 8 further comprising: stopping to impose said goodness measurelevel prior to changing said MCS; and reducing said correction factor bya predetermined value if said goodness measure estimation issubstantially less than or equal to a minimal goodness measure level.10. The method of claim 8, wherein said selection of MCS is performedbased on CQI obtained with non-decreased transmission power.
 11. Themethod of claim 1, further comprising: assigning confidence levels topackets; assigning a corresponding safety guard to each of saidconfidence levels; and adding said safety guard to said correctionfactor.
 12. The method of claim 11, further comprising imposing goodnessmeasure level in case said goodness measure estimation is substantiallyless than or equal to a minimal goodness measure level, whiletransmitting packets with low confidence level.
 13. The method of claim1, wherein said goodness measure is selectable from a list comprising:packet error rate (PER) and a combination of said PER and throughput.14. The method of claim 1, wherein a plurality of said correctionfactors is calculated and used, each for a corresponding transmissionmode.
 15. The method of claim 1, further comprising calculating andusing a plurality of said correction factors, each for a correspondingMCS.
 16. The method of claim 1, further comprising filtering saidcorrection factor.
 17. The method of claim 1, further comprisingallowing goodness measure levels that result in data loss in pre-definedperiods in which valuable data is not transmitted.
 18. A system forbackoff correction of channel quality information (CQI), the systemcomprising: a CQI estimation module to obtain CQI; a backoff adaptationmodule to get a goodness measure estimation and to calculate acorrection factor based on said goodness measure; and a modulation andcoding scheme (MCS) selection module to use said CQI adjusted by saidcorrection factor for selection of MCS.
 19. The system of claim 18wherein said backoff adaptation module to calculate said correctionfactor by: storing a plurality of tables each describing channel qualitydependency on said goodness measure for one of said MCSs; obtainingcurrent CQI from said CQI estimation module for current MCS atsubstantially the same time as said goodness measure estimation;estimating channel quality based on said goodness measure estimation andon a table from said plurality of tables corresponding to said currentMCS to get unbiased channel quality estimation; and calculating saidcorrection factor by subtracting said unbiased channel qualityestimation from said current CQI.
 20. The system of claim 18 whereinsaid backoff adaptation module to calculate said correction factor basedon a previous value of said correction factor and on a correctionfunction relating correction factor changes to goodness measureestimations.
 21. The system of claim 20 wherein each MCS has acorresponding correction function.
 22. The system of claim 20 whereinthe correction function is in the form of increasing said correctionfactor by a first constant if said goodness measure estimation is abovesaid first threshold, decreasing said correction factor by a secondconstant if said goodness measure estimation is below said secondthreshold and leave said correction factor unchanged otherwise.
 23. Thesystem of claim 18 wherein said backoff adaptation module to impose agoodness measure level in case said goodness measure estimation issubstantially less than or equal to a minimal goodness measure level.24. The system of claim 23 wherein said backoff adaptation module toimpose a goodness measure level by decreasing said correction factor.25. The system of claim 23 further comprising: at least one gain blockto amplify power of at least one signal transmitted by at least oneantenna according to a control signal received from said backoffadaptation module, wherein said backoff adaptation module to impose agoodness measure level by changing said control signal and thus changingtransmission power. stop imposing said goodness measure level prior tochanging said MCS; and reduce said correction factor by a predeterminedvalue if said goodness measure estimation is substantially less than orequal to a minimal goodness measure level, when said timer expires. 26.The system of claim 25 wherein said MCS selection module to use CQIobtained with non-decreased transmission power for said selection ofMCS.
 27. The system of claim 18, wherein said backoff adaptation moduleto: obtain confidence levels assigned to packets; assign a correspondingsafety guard to each of said confidence levels; and add said safetyguard to said correction factor.
 28. The system of claim 27, whereinsaid backoff adaptation module to impose goodness measure level in casesaid goodness measure estimation is substantially less than or equal toa minimal goodness measure level, while transmitting packets with lowconfidence level.
 29. The system of claim 18, wherein said goodnessmeasure is selectable from a list comprising: packet error rate (PER)and a combination of said PER and throughput.
 30. The system of claim18, wherein said backoff adaptation module to calculate and use aplurality of said correction factors, each for a correspondingtransmission mode.
 31. The system of claim 18, wherein said backoffadaptation module to calculate and use a plurality of said correctionfactors, each for a corresponding MCS.
 32. The system of claim 18,further comprising a filter to filter said correction factor.
 33. Thesystem of claim 23, wherein said backoff adaptation module to impose agoodness measure levels that may result in data loss in pre-definedperiods in which valuable data is not transmitted.